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Living organisms transmit signals through local interactions with their neighbors. However, the precise timing of signals is fundamentally challenged by the presence of numerous stochastic reactions within interacting cells. Here we develop a minimal model to investigate the strength of signal propagation in stochastic environments. We uncover a multimodal frequency dependency with a few local optima, which is robust in both one and two dimensions. Through mathematical analysis we explain the frequency dependency and uncover the interplay between stochasticity and external frequency in order to optimize the signaling strength of the system. Finally we investigate the possibilities of bidirectional reactions in the oscillating source, allowing us to define thermodynamic properties of the system and investigate the relationship between free-energy dissipation and precision of signaling, showing nontrivial frequency dependency in coupled cells.

During neuronal activity, the extracellular concentration of potassium ions ([K+]o) increases substantially above resting levels, yet it remains unclear what role these [K+]o changes play in the dendritic integration of synaptic inputs. We here used mathematical formulations and biophysical modeling to explore the role of synaptic activity-dependent K+ changes in dendritic segments of a visual cortex pyramidal neuron, receiving inputs tuned to stimulus orientation. We found that the spatial arrangement of inputs dictates the magnitude of [K+]o changes in the dendrites: Dendritic segments receiving similarly tuned inputs can attain substantially higher [K+]o increases than segments receiving diversely tuned inputs. These [K+]o elevations in turn increase dendritic excitability, leading to more robust and prolonged dendritic spikes. Ultimately, these local effects amplify the gain of neuronal input-output transformations, causing higher orientation-tuned somatic firing rates without compromising orientation selectivity. Our results suggest that local, activity-dependent [K+]o changes in dendrites may act as a "volume knob" that determines the impact of synaptic inputs on feature-tuned neuronal firing.